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Risk Model Analyst

3 weeks ago

Toronto, Ontario, Canada RBC Full time

About the Role

The Risk Model Analyst will play a key role in developing and enhancing data-driven models that assess client risk scores as part of the Anti-Money Laundering (AML) program. This position focuses on data analysis, feature engineering, and machine learning techniques to improve the accuracy and efficiency of client risk classification while ensuring regulatory compliance.

By working with structured financial data and risk indicators, the successful candidate will support the design, implementation, and monitoring of risk assessment models that help detect and prevent financial crimes.

Key Responsibilities

  • Support the development of client risk rating models by applying statistical methods and machine learning techniques to analyze customer risk factors.
  • Perform data extraction, cleansing, and transformation using SQL and Python to prepare datasets for modeling.
  • Implement basic machine learning models (e.g., logistic regression, decision trees, random forests) to improve risk classification.
  • Monitor model performance and assist in fine-tuning models by adjusting risk factors and thresholds.
  • Work with large-scale structured datasets (e.g., customer profiles, transaction histories) to identify key risk indicators.
  • Assist in feature engineering by integrating client attributes, geographic risks, and transaction behaviors into risk models.
  • Collaborate with compliance and regulatory teams to ensure models align with AML/KYC policies and reporting requirements.
  • Create reports and dashboards to visualize risk trends and model results for business stakeholders.
  • Document model assumptions, limitations, and validation processes to support regulatory audits and governance requirements.